Another example of Survivorship bias

Last week, I met a friend who told me that "No one returns alive from ____ hospital". That hospital being one of the three big branded hospitals of Hyderabad where another friend's wife was in critical condition.
That statement caught me off guard. He further mentioned that he knew 5 people who were admitted there but no one ever returned back alive.

I also knew one more fact that one of the other Big branded hospitals had refused to take the case of the friend's wife.

Knowing this, I argued that, maybe this hospital being one of the biggest ones in Hyderabad has a more risk taking ability for the type and condition of the patients. After all, if all the different entities are the same, then there is no real democracy and no decision making and no differentiation.

Just giving an example. Maybe, they wanted to give one last chance to even a 5-10% chance which other people refuse compared to others who give a chance maybe only to 50% and above.

This high risk input could cause the statistic that my friend was quoting.

I wanted to relate this incident and my thought process to a story I have come across previously from World war.

During World War II, a statistician named Abraham Wald used survivorship bias to determine where to reinforce returning aircraft with armor. While military leaders initially wanted to add armor to the areas with the most bullet holes (like the wings and fuselage), Wald realized that these were precisely the areas where a plane could sustain damage and still return. He argued that armor should be added to the areas with few or no bullet holes, such as the engines and cockpit, because planes hit there were unlikely to survive and return to base.

https://en.wikipedia.org/wiki/Survivorship_bias

The concept of Survivorship bias is there in both. 

Now, imagine this friend with this bias taking a decision on someone's life. They would never get the 5-10% chance the big hospital was willing to give.